A Survey on Botnets Attack Detection Utilizing Machine and Deep Learning Models

Botnets can be a major risk to computer networks, as they attack in dangerous and diverse ways. They are becoming increasingly challenging due to the massive amount of network devices and the obfuscation of communication protocols. This paper provides a critical review and analysis of the recent Machine Learning based models for detecting botnet attacks. It explains the used methodologies, datasets, validation methods, and detection metrics. This paper also identifies the current gaps and limitations to provide recommendations for future research directions in this field. This survey can be used as a guide for new researchers to enhance this research area.